Top Remote Data & Analytics Jobs in Reno, NV

Support FAA by developing, reviewing, and documenting metrics and dashboards for the National Airspace System. Work with large aviation datasets to perform data quality checks, queries, and automation. Create documentation, user guides, Confluence uploads, presentations, and reports for FAA leadership and industry stakeholders.

Perform sponsorship valuations through research, data modeling, analysis, and client presentations. Maintain valuation database, surface insights, refine methodology, and support strategy projects to inform sponsorship proposals and renewals.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

Serve as the bridge between business stakeholders and development for internal data initiatives. Own intake, discovery, and requirements documentation for analytics, BI, and reporting. Write user stories, acceptance criteria, data definitions, and reporting logic. Maintain a prioritized backlog, support stakeholder validation of prototypes, participate in agile ceremonies, and resolve requirement gaps and risks to ensure development can execute independently.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

Support Ivanti ITSM/Neurons implementation by designing ETL and data migration, cleansing and mapping legacy asset records into a CMDB, building SQL reports and KPIs, validating data quality and integrations, supporting UAT, documenting processes and training staff, and participating in Agile sprints to optimize ITAM workflows.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

Perform hands-on data engineering to assess legacy sources, profile and cleanse data, design and run ETL/ELT migrations into Azure Government environments, validate and reconcile migrated data, implement data quality checks and basic governance, and prepare curated datasets for analytics (Power BI) while coordinating with application teams and producing contract deliverables.

Lead architecture and delivery of scalable ELT pipelines and data models using tools like Databricks, dbt, and Airflow. Build self-serve analytics products and BI solutions, drive data governance and observability, partner with data scientists and stakeholders, and develop frameworks (including AI-driven tooling) that enable data discoverability, reliability, and business impact.